The Transregional Collaborative Research Centre 161 “Quantitative Methods for Visual Computing” is an interdisciplinary research centre at the University of Stuttgart and the University of Konstanz, funded by Deutsche Forschungsgemeinschaft (DFG) under project number 251654672. Ulm University and Ludwig-Maximilians-Universität München are participating institutions in the second and third funding period. The Max Planck Institute for Biological Cybernetics in Tübingen in was a participating institution in the first funding period.

The goal of SFB/Transregio 161 is establishing the paradigm of quantitative science in the field of visual computing, which is a long-term endeavour requiring a fundamental research effort broadly covering four research areas, namely quantitative models and measures, adaptive algorithms, interaction and applications. In the third funding period, which started in 2023, new research directions are being approached. One is visual explainability, assessing and quantifying how well the users of a visualisation system understand the phenomena shown visually. The second direction targets mixed reality, covering all forms of augmented and virtual reality as a cross-cutting field of various visual computing subfields, irrespective of applied technology. The third research theme aims to bring research results in the world, moving away from experiments in the laboratory and in the wild to openly accessible applications that provide research results, methods, data sets, and other outcomes from SFB/Transregio 161 to a wide range of stakeholders in academia, industry, teaching, and society in general.

In SFB/Transregio 161, approximately 40 scientists in the fields of computer science, visualisation, computer vision, human computer interaction, linguistics and applied psychology are jointly working on improving the quality of future visual computing methods and applications.

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1 to 10 of 49 Results
Oct 25, 2024 - SFB-TRR 161 A08 "A Learning-Based Research Methodology for Visualization"
Angerbauer, Katrin; Van Wagoner, Phoenix; Halach, Tim; Vogelsang, Jonas; Hube, Natalie; Smith, Andria Lenae; Keplinger, Ksenia; Sedlmair, Michael, 2024, "Supplemental Material for the Paper: Is it Part of Me? Exploring Experiences of Inclusive Avatar Use For Visible and Invisible Disabilities in Social VR", https://doi.org/10.18419/darus-4426, DaRUS, V1
Supplemental Material for the paper titled: " Is it Part of Me? Exploring Experiences of Inclusive Avatar Use For Visible and Invisible Disabilities in Social VR" accepted for presentation at the ASSETS'24 conference. The structure of the folder is as following: . └── avatars...
Sep 16, 2024 - SFB-TRR 161 C06 "User-Adaptive Mixed Reality"
Chiossi, Francesco; Haliburton, Luke; Ou, Changkun; Butz, Andreas; Schmidt, Albrecht, 2024, "Dataset for "Short-Form Videos Degrade Our Capacity to Retain Intentions: Effect of Context Switching On Prospective Memory"", https://doi.org/10.18419/darus-3327, DaRUS, V1, UNF:6:7FzpUkbNmyXLFXVYJ8abKQ== [fileUNF]
Social media platforms use short, highly engaging videos to catch users’ attention. While the short-form video feeds popularized by TikTok are rapidly spreading to other platforms, we do not yet understand their impact on cognitive functions. We conducted a between-subjects exper...
Sep 16, 2024 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"
Evers, Marina; Weiskopf, Daniel, 2024, "Supplementary Material for Uncertainty-aware Spectral Visualization", https://doi.org/10.18419/darus-4447, DaRUS, V1
In this supplemental material, we provide supplemental information (PDF document with derivations of the results presented in the paper and two additional use cases) and the supplementary video for uncertainty-aware spectral analysis. We model an uncertain time series as a multiv...
Sep 2, 2024 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"
Reichmann, Luca; Hägele, David; Weiskopf, Daniel, 2024, "Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions", https://doi.org/10.18419/darus-4441, DaRUS, V1, UNF:6:WoQ4MNffz92VcvZ/qCGL5w== [fileUNF]
This dataset contains the supplemental material for "Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions". The contents and usage of this dataset are described in the README.md files.
Aug 20, 2024 - SFB-TRR 161 INF "Collaboration Infrastructure"
Müller, Christoph, 2024, "SFB/Transregio 161 Data Management Plan 2023-2027", https://doi.org/10.18419/darus-4452, DaRUS, V1
The participating universities in SFB/Transregio 161 acknowledge the general importance of re-search data management as a vital issue for all of their work and provide increasing central sup-port for long-term accessibility and reusability of data, documentation of methods and to...
Jul 30, 2024 - Visualisierungsinstitut der Universität Stuttgart
Gralka, Patrick; Müller, Christoph; Heinemann, Moritz; Reina, Guido; Weiskopf, Daniel; Ertl, Thomas, 2024, "Supplemental Material for "Power Overwhelming: The One With the Oscilloscopes"", https://doi.org/10.18419/darus-4256, DaRUS, V1, UNF:6:+e/WFL9E6WB+2FvGNOvcGA== [fileUNF]
Supplemental Material for "Power Overwhelming: The One With the Oscilloscopes". Contains the aggregated energy consumption data from the experiments in the paper. The application under test was MegaMol with two OpenGL-based sphere rasterization rendering methods (data static on G...
Jun 21, 2024 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences"
Bienroth, Denis; Charitakis, Natalie; Jaeger-Honz, Sabrina; Garkov, Dimitar; Elliott, David; Porrello, Enzo R.; Klein, Karsten; Nim, Hieu T.; Schreiber, Falk; Ramialison, Mirana, 2024, "Spatially Resolved Transcriptomics Mining in 3D and Virtual Reality Environments with VR-Omics (Software and Data)", https://doi.org/10.18419/darus-4254, DaRUS, V1
Here, we summarise available data and source code regarding the publication "Spatially Resolved Transcriptomics Mining in 3D and Virtual Reality Environments with VR-Omics". Abstract Spatially resolved transcriptomics (SRT) technologies produce complex, multi-dimensional data set...
Jun 19, 2024 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences"
Jaeger-Honz, Sabrina; Klein, Karsten; Schreiber, Falk, 2024, "Research Data Summary for: "Systematic analysis, aggregation and visualisation of interaction fingerprints for molecular dynamics simulation data"", https://doi.org/10.18419/darus-4251, DaRUS, V1
Here, we summarise available data and source code regarding the publication "Systematic analysis, aggregation and visualisation of interaction fingerprints for molecular dynamics simulation data". Abstract Computational methods such as molecular docking or molecular dynamics (MD)...
Jun 18, 2024 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences"
Kern, Martin; Jaeger-Honz, Sabrina; Schreiber, Falk; Sommer, Björn, 2024, "Research Data: "APL@voro—interactive visualization and analysis of cell membrane simulations"", https://doi.org/10.18419/darus-4252, DaRUS, V1
Here, we summarise available data and source code regarding the publication "APL@voro—interactive visualization and analysis of cell membrane simulations". Abstract Molecular dynamics (MD) simulations of cell membranes allow for a better understanding of complex processes such as...
Apr 8, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Bulling, Andreas, 2024, "VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)", https://doi.org/10.18419/darus-3138, DaRUS, V1, UNF:6:NwphGtoYrBQqd2TyRh0OHA== [fileUNF]
This dataset contains stimuli and collected participant data of VisRecall++. The structure of the dataset is described in the README-File. Further, if you are interested in related codes of the publication, you can find a copy of the code repository (see Metadata for Research Sof...
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